The field of the disclosure relates generally to wind turbine generators and, more particularly, to a system and method for operation of wind turbine parks through enhanced acoustic measurements.
Most known wind turbine generators include a rotor having multiple blades. The rotor is sometimes coupled to a housing, or nacelle, that is positioned on top of a base, for example, a tubular tower. At least some known utility grade wind turbines, i.e., wind turbines designed to provide electrical power to a utility grid have rotor blades having predetermined shapes and dimensions. The rotor blades transform mechanical wind energy into induced blade lift forces that further induce a mechanical rotational torque that drives one or more generators, subsequently generating electric power. A plurality of wind turbine generators in a localized geographic array is typically referred to as a wind farm or a wind park.
During operation of such known wind parks, rotational transiting of the rotor blades through air generates aerodynamic acoustic emissions, or noise. As a consequence, at least some of these known wind parks will receive noise receptor devices in the vicinity of the wind parks to measure the overall noise level. At least some of such measured acoustic noises have a decibel (dB) level that may approach local regulatory levels. To comply with the limits, at least some of the wind turbines may need to be put into a noise reduced operation (NRO) mode for a period of time. As such, the reduction of noise comes at the cost of annual energy production (AEP). Therefore, it is necessary to apply NROs that most efficiently reduce the noise levels for the least amount of time, and apply to the minimum number of turbines in the wind park to achieve the desired acoustic levels.
Known methods to achieve regulatory compliance include using far-field sound propagation models based on certain site parameters, e.g., turbine-receptor distances, ground absorption, wind shear, and thermal gradients together with a model of the turbine noise. However, conservative parameters may be selected that unnecessarily restrict production.
Another known method includes directly measuring the acoustic environment in the vicinity of the wind park and using feedback control to regulate the wind turbines in and out of NRO mode while taking into account time-dependent changes in the turbine noise level, e.g., air density, blade contamination state, wind shear, and the propagation characteristics. However, such measurement based control lacks features to discriminate whether the measured noise is actually originating from the wind turbines or is contaminated with, and possibly dominated by, ambient sounds. The latter condition typically results in a distorted sound pressure level (SPL) estimate, and the feedback control features would then attempt to reduce wind turbine noise through NRO even though the wind turbine noise levels are well within the established parameters. Therefore, feedback control setups (as well as processing certification measurements) need to include examinations of voluminous acoustic measurements to identify and discard acoustic records contaminated by extraneous noise contributions, e.g., cars, planes, and birds. These activities typically involve lengthy listening checks and manual removal of the contaminated segments. As such, the most severe noise outliers can be easily identified and discarded by inspecting the dB difference between the measured noise and the peak of the expected wind turbine noise curve, or the full curve if the wind speed/rpm is known. However, the SPL variations at large distances due to propagation effects introduce a substantial uncertainty when applying only this kind of filtering, thereby decreasing the usefulness of the data.